Abstract

SummaryBackgroundα-fetoprotein (AFP) response has been proven a key tumor marker for hepatocellular carcinoma (HCC), but its definition remains controversial. This study aims to characterize AFP trajectories after transarterial chemoembolization (TACE) and examine its impact on clinical outcomes.MethodsThis longitudinal, multicenter, retrospective, cohort study examined data from the electronic medical record system of four hospitals in China between January 1, 2007 to December 31, 2016. A latent class growth mixed model was applied to distinguish potential AFP dynamic changing trajectories. The multivariable Cox models were used to calculate adjusted hazard ratios (aHRs) and 95% CIs for overall survival. Inverse-probability-of-treatment weighted analyses were performed to eliminate unmeasured confounders through marginal structural models.FindingsA total of 881 patients, who had intermediate-stage HCC with AFP repeatedly measured 3 to 10 times, were included in the study. Three distinct trajectories were identified using the latent class growth mixture model: high-rising (25.7%; n = 226), low-stable (58.7%; n = 517), and sharp-falling (AFP serological response, 15.6%; n = 138). Compared with the low-stable class, the aHRs for death were 5.13 (3.71, 7.10) and 0.52 (0.33, 0.81) for the high-rising and sharp-falling class, adjusted by gender, baseline major tumor size, intrahepatic lesions number, and logAFP(smooth). Furthermore, high-rising class had a significantly higher HR in the subgroup of female patients (10.60, 95%CI: 6.29, 17.86), age<55 (6.78, 95%CI: 4.79, 9.59) and Child-Pugh class B (23.01, 95%CI:8.07, 65.63) (P = 0.014, 0.046 and 0.033 for interaction, respectively). Trajectories of AFP had the highest relative importance of each parameter to survival, including largest tumor size, intrahepatic lesions number, Child-Pugh class, and baseline AFP.InterpretationAFP trajectories were associated with overall survival for intermediate-stage HCC after TACE.FundingThe Natural Science Foundation of Fujian Province (Nos. 2018J01352, 2016J01576 and 2016J01586); the Science and Technology Innovation Joint Foundation of Fujian Province (Nos. 2017Y9125).

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